Methods and apparatus for detecting structural, perfusion, and functional abnormalities

ABSTRACT

A method for obtaining data includes scanning a lung of a patient with a Multi-Energy Computed Tomography (MECT) system to acquire data regarding a plurality of contrast agents.

BACKGROUND OF THE INVENTION

[0001] This invention relates to computed tomographic (CT) imaging, andmore particularly to methods and apparatus for the detection anddiagnosis of lung abnormalities.

[0002] In spite of recent advancements in computed tomography (CT)technology, such as faster scanning speeds, larger coverage withmultiple detector rows, and thinner slices, energy resolution is still amissing piece. Namely, wide x-ray photon energy spectrum from the x-raysource and the lack of energy resolution from CT detection systemspreclude energy discrimination CT.

[0003] X-ray attenuation through a given object is not a constant.Rather, the X-ray attenuation is strongly dependent on the x-ray photonenergy. This physical phenomenon manifests itself in the image asbeam-hardening artifacts, such as, nonuniformity, shading, and streaks.Some beam-hardening artifacts can be easily corrected, but otherbeam-hardening artifacts may be more difficult to correct. In general,known methods to correct beam hardening artifacts include watercalibration, which includes calibrating each CT machine to remove beamhardening from materials similar to water, and iterative bonecorrection, wherein bones are separated in the first-pass image thencorrecting for beam hardening from the bones in the second-pass.However, beam hardening from materials other than water and bone, suchas metals and contrast agents, may be difficult to correct. In addition,even with the above described correction methods, conventional CT doesnot provide quantitative image values. Rather, the same material atdifferent locations often shows different CT numbers.

[0004] Another drawback of conventional CT is a lack of materialcharacterization. For example, a highly attenuating material with a lowdensity can result in the same CT number in the image as a lessattenuating material with a high density. Thus, there is little or noinformation about the material composition of a scanned object is basedsolely on the CT number. At least some state-of-the-art CT scannerscurrently available are limited to providing anatomical information. Forlung scans, images produced by such scanners exhibit a significant levelof image artifacts and CT number inaccuracy. These limitations preventthe utilization of the CT device for advanced diagnosis. Accordingly,the methods and apparatus described herein address the detection anddiagnosis of lung abnormalities.

BRIEF DESCRIPTION OF THE INVENTION

[0005] In one aspect, a method for obtaining data is provided. Themethod includes scanning a lung of a patient with a Multi-EnergyComputed Tomography (MECT) system to acquire data regarding a pluralityof contrast agents

[0006] In another aspect, a Multi-Energy Computed Tomography (MECT)System is provided. The MECT includes a radiation source, a radiationdetector, and a computer operationally coupled to the radiation sourceand the radiation detector. The computer is configured to receive dataregarding a first energy spectrum of a scan of a lung of a patient,receive data regarding a second energy spectrum of the scan of the lung,generating a first functional image using data regarding a firstcontrast agent, and generating a second functional image using dataregarding a second contrast agent.

[0007] In yet another aspect, a Multi-Energy Computed Tomography (MECT)System is provided. The MECT includes a radiation source, a radiationdetector, and a computer operationally coupled to the radiation sourceand the radiation detector. The computer is configured to receive dataregarding a first energy spectrum of a scan of a lung of a patient,receive data regarding a second energy spectrum of the scan, anddecompose the received data to generate data regarding a plurality ofcontrast agents.

[0008] In still another aspect, a computer readable medium is encodedwith a program. The program is configured to instruct a computer toreceive data regarding a first energy spectrum of a scan of a lung of apatient, receive data regarding a second energy spectrum of the scan,and decompose the received data to generate data regarding a pluralityof contrast agents.

[0009] In yet still another aspect, a computer readable medium isencoded with a program. The program is configured to instruct a computerto scan a lung of a patient with a Multi-Energy Computed Tomography(MECT) system to acquire data regarding a first contrast agent in agaseous medium and a second contrast agent in a liquid medium, generatea first functional image using data regarding the first contrast agent,and generate a second functional image using data regarding the secondcontrast agent.

[0010] In another aspect a method for obtaining data is provided. Themethod includes administering a gaseous contrast agent to a patient,administering a liquid contrast agent to the patient, and imaging thepatient to obtain data regarding the gaseous contrast agent and theliquid contrast agent.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011]FIG. 1 is a pictorial view of a MECT imaging system.

[0012]FIG. 2 is a block schematic diagram of the system illustrated inFIG. 1.

[0013]FIG. 3 is a flow chart representing a pre-reconstruction analysis.

[0014]FIG. 4 is a flow chart representing a post-reconstructionanalysis.

[0015]FIG. 5 is a schematic view of Lung Ventilation and Perfusionsystems.

[0016]FIG. 6 illustrates examples of ventilation perfusion maps.

[0017]FIG. 7 illustrates an example where a V/Q map has light gray areasthat indicate ventilation is less than perfusion.

[0018]FIG. 8 illustrates an example where areas of very dark colorindicate that perfusion is less than ventilation.

DETAILED DESCRIPTION OF THE INVENTION

[0019] The methods and apparatus described herein address the detectionand diagnosis of abnormalities in the lung regions of a patient byemploying novel approaches that make use of basic properties of thex-ray and material interaction. For each ray trajectory, multiplemeasurements regarding different mean x-ray energies are acquired. Asexplained in greater detail below, when Basis Material Decomposition(BMD) and Compton and photoelectric decomposition are performed on thesemeasurements, additional information is obtained that enables improvedaccuracy and characterization.

[0020] In some known CT imaging system configurations, an x-ray sourceprojects a fan-shaped beam which is collimated to lie within an X-Yplane of a Cartesian coordinate system and generally referred to as an“imaging plane”. The x-ray beam passes through an object being imaged,such as a patient. The beam, after being attenuated by the object,impinges upon an array of radiation detectors. The intensity of theattenuated radiation beam received at the detector array is dependentupon the attenuation of an x-ray beam by the object. Each detectorelement of the array produces a separate electrical signal that is ameasurement of the beam intensity at the detector location. Theintensity measurements from all the detectors are acquired separately toproduce a transmission profile.

[0021] In third generation CT systems, the x-ray source and the detectorarray are rotated with a gantry within the imaging plane and around theobject to be imaged such that the angle at which the x-ray beamintersects the object constantly changes. A group of x-ray attenuationmeasurements, i.e., projection data, from the detector array at onegantry angle is referred to as a “view”. A “scan” of the objectcomprises a set of views made at different gantry angles, or viewangles, during one revolution of the x-ray source and detector.

[0022] In an axial scan, the projection data is processed to constructan image that corresponds to a two-dimensional slice taken through theobject. One method for reconstructing an image from a set of projectiondata is referred to in the art as the filtered backprojection technique.This process converts the attenuation measurements from a scan intointegers called “CT numbers” or “Hounsfield units” (HU), which are usedto control the brightness of a corresponding pixel on a cathode ray tubedisplay.

[0023] To reduce the total scan time, a “helical” scan may be performed.To perform a “helical” scan, the patient is moved while the data for theprescribed number of slices is acquired. Such a system generates asingle helix from a fan beam helical scan. The helix mapped out by thefan beam yields projection data from which images in each prescribedslice may be reconstructed.

[0024] Reconstruction algorithms for helical scanning typically usehelical weighing algorithms that weight the collected data as a functionof view angle and detector channel index. Specifically, prior to afiltered backprojection process, the data is weighted according to ahelical weighing factor, which is a function of both the gantry angleand detector angle. The weighted data is then processed to generate CTnumbers and to construct an image that corresponds to a two-dimensionalslice taken through the object.

[0025] To further reduce the total acquisition time, multi-slice CT hasbeen introduced. In multi-slice CT, multiple rows of projection data areacquired simultaneously at any time instant. When combined with helicalscan mode, the system generates a single helix of cone beam projectiondata. Similar to the single slice helical, weighting scheme, a methodcan be derived to multiply the weight with the projection data prior tothe filtered backprojection algorithm.

[0026] As used herein, an element or step recited in the singular andproceeded with the word “a” or “an” should be understood as notexcluding plural said elements or steps, unless such exclusion isexplicitly recited. Furthermore, references to “one embodiment” of thepresent invention are not intended to be interpreted as excluding theexistence of additional embodiments that also incorporate the recitedfeatures.

[0027] Also as used herein, the phrase “reconstructing an image” is notintended to exclude embodiments of the present invention in which datarepresenting an image is generated but a viewable image is not. However,many embodiments generate (or are configured to generate) at least oneviewable image.

[0028] Herein are described methods and apparatus for detectingstructural, perfusion, and functional abnormalities in lung tissue usingan energy-discriminating (also known as multi-energy) computedtomography (MECT) system. First described is MECT system 10 and followedby lung applications using MECT system 10.

[0029] Energy Discrimination (Multi-Energy) CT System 10

[0030] Referring to FIGS. 1 and 2, a multi-energy scanning imagingsystem, for example, a multi-energy multi-slice computed tomography(MECT) imaging system 10, is shown as including a gantry 12representative of a “third generation” CT imaging system. As usedherein, a multi-energy computed tomography system may also be referredto as an energy discrimination CT (EDCT) system. Gantry 12 has an x-raysource 14 that projects a beam of x-rays 16 toward a detector array 18on the opposite side of gantry 12. Detector array 18 is formed by aplurality of detector rows (not shown) including a plurality of detectorelements 20 which together sense the projected x-rays that pass throughan object, such as a medical patient 22. Each detector element 20produces an electrical signal that represents the intensity of animpinging x-ray beam and hence can be used to estimate the attenuationof the beam as it passes through object or patient 22. During a scan toacquire x-ray projection data, gantry 12 and the components mountedtherein rotate about a center of rotation 24. FIG. 2 shows only a singlerow of detector elements 20 (i.e., a detector row). However, multi-slicedetector array 18 includes a plurality of parallel detector rows ofdetector elements 20 such that projection data corresponding to aplurality of quasi-parallel or parallel slices can be acquiredsimultaneously during a scan.

[0031] Rotation of components on gantry 12 and the operation of x-raysource 14 are governed by a control mechanism 26 of MECT system 10.Control mechanism 26 includes an x-ray controller 28 that provides powerand timing signals to x-ray source 14 and a gantry motor controller 30that controls the rotational speed and position of components on gantry12. A data acquisition system (DAS) 32 in control mechanism 26 samplesanalog data from detector elements 20 and converts the data to digitalsignals for subsequent processing. An image reconstructor 34 receivessampled and digitized x-ray data from DAS 32 and performs high-speedimage reconstruction. The reconstructed image is applied as an input toa computer 36, which stores the image in a storage device 38. Imagereconstructor 34 can be specialized hardware or computer programsexecuting on computer 36.

[0032] Computer 36 also receives commands and scanning parameters froman operator via console 40 that has a keyboard. An associated cathoderay tube display 42 allows the operator to observe the reconstructedimage and other data from computer 36. The operator supplied commandsand parameters are used by computer 36 to provide control signals andinformation to DAS 32, x-ray controller 28, and gantry motor controller30. In addition, computer 36 operates a table motor controller 44, whichcontrols a motorized table 46 to position patient 22 in gantry 12.Particularly, table 46 moves portions of patient 22 through gantryopening 48.

[0033] In one embodiment, computer 36 includes a device 50, for example,a floppy disk drive, CD-ROM drive, DVD drive, magnetic optical disk(MOD) device, or any other digital device including a network connectingdevice such as an Ethernet device for reading instructions and/or datafrom a computer-readable medium 52, such as a floppy disk, a CD-ROM, aDVD, a MOD or an other digital source such as a network or the Internet,as well as yet to be developed digital means. Computer 36 is programmedto perform functions described herein, and as used herein, the termcomputer is not limited to just those integrated circuits referred to inthe art as computers, but broadly refers to computers, processors,microcontrollers, microcomputers, programmable logic controllers,application specific integrated circuits, and other programmablecircuits, and these terms are used interchangeably herein. CT imagingsystem 10 is an energy-discriminating (also known as multi-energy)computed tomography (MECT) system in that system 10 is configured to beresponsive to different x-ray spectra. This can be accomplished with aconventional third generation CT system to acquire projectionssequentially at different x-ray tube potentials. For example, two scansare acquired either back to back or interleaved in which the tubeoperates at 80 kVp and 160 kVp potentials, for example. Alternatively,special filters are placed between the x-ray source and the detectorsuch that different detector rows collect projections of different x-rayenergy spectrum. Alternatively, the special filters that shape the x-rayspectrum can be used for two scans that are acquired either back to backor interleaved. Yet another embodiment is to use energy sensitivedetectors such that each x-ray photon reaching the detector is recordedwith its photon energy. Although the specific embodiment mentioned aboverefers to a third generation CT system, the methods described hereinequally apply to fourth generation CT systems (stationarydetector—rotating x-ray source) and fifth generation CT systems(stationary detector and x-ray source).

[0034] There are different methods to obtain multi-energy measurements:(1) scan with two distinctive energy spectra, (2) detect photon energyaccording to energy deposition in the detector, and (3) photon counting.Photon counting provides clean spectra separation and an adjustableenergy separation point for balancing photon statistics.

[0035] MECT facilitates reducing or eliminating a plurality of problemsassociated with conventional CT, such as, but not limited to, a lack ofenergy discrimination and material characterization. In the absence ofobject scatter, one only need system 10 to separately detect two regionsof photon energy spectrum: the low-energy and the high-energy portionsof the incident x-ray spectrum. The behavior at any other energy can bederived based on the signal from the two energy regions. This phenomenonis driven by the fundamental fact that in the energy region wheremedical CT is interested, two physical processes dominate the x-rayattenuation: (1) Compton scatter and the (2) photoelectric effect. Thus,detected signals from two energy regions provide sufficient informationto resolve the energy dependence of the material being imaged.Furthermore, detected signals from two energy regions provide sufficientinformation to determine the relative composition of an object composedof two materials.

[0036] In an exemplary embodiment, MECT uses a decomposition algorithm,such as, but not limited to, a CT number difference algorithm, a Comptonand photoelectric decomposition algorithm, a basis materialdecomposition (BMD) algorithm, and a logarithm subtraction decomposition(LSD) algorithm.

[0037] The CT number difference algorithm includes calculating adifference value in a CT or a Hounsfield number between two imagesobtained at different tube potentials. In one embodiment, the differencevalues are calculated on a pixel-by-pixel basis. In another embodiment,average CT number differences are calculated over a region of interest.The Compton and photoelectric decomposition algorithm includes acquiringa pair of images using MECT 10, and separately representing theattenuations from Compton and photoelectric processes. The BMD algorithmincludes acquiring two CT images, wherein each image represents theequivalent density of one of the basis materials. Since a materialdensity is independent of x-ray photon energy, these images areapproximately free of beam-hardening artifacts. Additionally, anoperator can choose the basis material to target a certain material ofinterest, thus enhancing the image contrast. In use, the BMD algorithmis based on the concept that the x-ray attenuation (in the energy regionfor medical CT) of any given material, can be represented by properdensity mix of other two given materials, accordingly, these twomaterials are called the basis materials. In one embodiment, using theLSD algorithm, the images are acquired with quasi-monoenergetic x-rayspectra, and the imaged object can be characterized by an effectiveattenuation coefficient for each of the two materials, therefore the LSDalgorithm does not incorporate beam-hardening corrections. Additionally,the LSD algorithm is not calibrated, but uses a determination of thetissue cancellation parameters, which are the ratio of the effectiveattenuation coefficient of a given material at the average energy ofeach exposure. In an exemplary embodiment, the tissue cancellationparameter is primarily dependent upon the spectra used to acquire theimages, and on any additional factors that change the measured signalintensity from that which would be expected for a pair of ideal,mono-energetic exposures.

[0038] It should be noted that in order to optimize a multi-energy CTsystem, the larger the spectra separation, the better the image quality.Also, the photon statistics in these two energy regions should besimilar, otherwise, the poorer statistical region will dominate theimage noise.

[0039] Lung Applications of Energy Discriminating using Multi-Energy CTSystem 10

[0040] The present invention applies the above principle to lungstudies. In specific, MECT system 10 is utilized to produce CT images asherein described. A pre-reconstruction analysis, a post-reconstructionanalysis, and a scout image analysis are three techniques that can beused with MECT system 10 for tissue characterization.

[0041]FIG. 3 is a flow chart representing a pre-reconstruction analysis54 wherein a decomposition 56 is accomplished prior to a reconstruction58. Computer 36 collects the acquired projection data generated bydetector array 18 (shown in FIG. 1) at discrete angular positions of therotating gantry 12 (shown in FIG. 1), and passes the signals to apreprocessor 60. Preprocessor 60 re-sorts the projection data receivedfrom computer 36 to optimize the sequence for the subsequentmathematical processing. Preprocessor 60 also corrects the projectiondata from computer 36 for detector temperature, intensity of the primarybeam, gain and offset, and other deterministic error factors.Preprocessor 60 then extracts data corresponding to a high-energy view62 and routes it to a high energy channel path 64, and routes the datacorresponding to a low-energy views 66 to a low energy path 68. Usingthe high energy data and low energy data, a decomposition algorithm isused to produce two streams of projection data, which are thenreconstructed to obtain two individual images pertaining to twodifferent materials.

[0042]FIG. 4 is a flow chart representing a post-reconstruction analysiswherein decomposition 56 is accomplished after reconstruction 58.Computer 36 collects the acquired projection data generated by detectorarray 18 (shown in FIG. 1) at discrete angular positions of rotatinggantry 12 (shown in FIG. 1), and routes the data corresponding tohigh-energy views 62 to high energy path 64 and routes the datacorresponding to low-energy views 66 to low energy path 68. A first CTimage 70 corresponding to the high-energy series of projections 62 and asecond CT image 72 corresponding to low-energy series of projections 66are reconstructed 58. Dual-energy decomposition 56 is then performedusing a decomposition algorithm to obtain two individual imagesrespectively, pertaining to two different materials. In scout imageanalysis, the signal flow can be similar to FIG. 3 or FIG. 4. However,the table is moved relative to the gantry to acquire the data.

[0043] One common cause of a ventilation perfusion mismatch is pulmonaryembolization. However, any cause of pulmonary artery obstruction(bronchogenic carcinoma, lymphoma, metastatic disease, sarcoma,aneurysm, sarcoid, and fungal or granulomatous infection) can producethe same findings. In some known clinical practices,ventilation-perfusion scans are acquired with limited spatial resolutionusing positron emission tomography (PET) requiring the injection ofradioactive isotopes. Similarly, dual scans are required which presentdifficulty in registering anatomy between the two scans, especially inthe case where the scan times or scan interval is long enough to createmotion-related artefacts. Multiple energy computed tomography (MECT)ventilation-perfusion maps are generated by simultaneously injecting IVcontrast, such as an ionic or non-ionic iodine-based (I) agent such asIopamidol, chelates of gadolinium such as Gd-DTPA, or non-ionic chelatessuch as gadodiamide (gadolinium-diethylenetriamine pentaacetic acidbismethylamide, C₁₆H₂₈GdN₅O₉×H₂O), to a patient while he/she inhales astable non-radioactive gas usually having a high atomic number and ordensity such as Xe¹³¹. A single scan is acquired and the ratio ofHounsfield units in CT pixel data reconstructed at each of multipleenergies provides a 3-dimensional ventilation-perfusion map. Theresulting image has significant clinical value. Two major applicationsare detection of pulmonary emboli and assessment of regional lungfunction. When a blood clot blocks a pulmonary artery, blood flow ceasesto the lung region normally supplied by that vessel, and a corresponding“perfusion defect” results. Such a defect manifest itself as a “high”signal in a ventilation/perfusion map as described below (V/Q map)indicating an area where oxygen exchange is inefficient.

[0044] In use, and in accordance with one embodiment, a patient breathesone full breath of Xe¹³¹ and a substantially simultaneous (timed) Bolusinjection of a contrast medium (I) is done. Multiple Energy CT scan datais collected with system 10 at Total Lung Capacity (TLC). The collecteddata is decomposed using one of the decomposition methods describedabove (CT Number Difference, Compton and Photoelectric Decomposition,Basis Material Decomposition, or Logarithm Subtraction Decomposition),MECT images are acquired with x-ray spectra or energy discrimination tohighlight the differences between the relevant atoms of the administeredcontrast agents (eg: Xe¹³¹ and I) The decomposition step yields twoimage data sets, one (the ventilation functional image, “V” image)emphasizing the density of Xe¹³¹; the other (the perfusion functionalimage, “Q” image) illustrating the density of I.

[0045] After the two functional images are generated, a V/Q signal fromthe images is calculated. In one embodiment, the two functional imagesare registered with each other and a V/Q signal is calculated on apixel-by-pixel basis, wherein the ratio of CT numbers in the V image tothe CT numbers of the Q image represents the V/Q signal for eachlocation in the two images. The V/Q map can be presented by displayingthe 3-dimensional lung anatomy via a traditional grayscale image withthe V/Q ratios superimposed using a colormap. The traditional grayscaleimage is an anatomical image and not a functional image. This providesan anatomical map of oxygen exchange efficiency. Using any combinationof the acquired images, V, Q, and/or V/Q map data, an observer orcomputer algorithm can highlight regions of suspicious V/Q. A computeraided detection or diagnosis algorithm can use the data to determinediagnosis of pathologies such as Chronic Obstructive Pulmonary Disease(COPD) and emphysema, or detect, quantify, and classify pathologicalregions of poor pulmonary function.

[0046]FIG. 5 is a schematic view of Lung Ventilation and Perfusionsystems showing an Arterial/Venous network on the left side of FIG. 5and an Airway/Bronchial network on the right side of FIG. 5.Abnormalities in either of these networks will result in V/Q mismatch,ratios inconsistent with the overall V/Q activity of the entirepulmonary anatomy.

[0047]FIG. 6 illustrates examples of ventilation perfusion mapsincluding a Perfusion Image showing a vascular network on the left side,a Ventilation Image with bronchial and alveolar network illustrated inthe middle, and a ratio of Middle to Left image (V/Q Map) on the rightside of FIG. 6. A medium gray area indicates ventilation and perfusionare matched. FIG. 7 illustrates an example where the V/Q map has lightgray areas that indicate ventilation is less than perfusion andpotential respiratory obstruction may exist. Similarly, FIG. 8illustrates an example where areas of very dark color indicate thatperfusion is less than ventilation and a potential for arterial blockageor pulmonary embolism may exist.

[0048] The herein described methods and apparatus facilitatecharacterizing lung tissue which facilitates the diagnosis ofabnormalities in an efficient and cost effective manner.

[0049] While the invention has been described in terms of variousspecific embodiments, those skilled in the art will recognize that theinvention can be practiced with modification within the spirit and scopeof the claims.

What is claimed is:
 1. A method for obtaining data, said methodcomprising scanning a lung of a patient with a Multi-Energy ComputedTomography (MECT) system to acquire data regarding a plurality ofcontrast agents.
 2. A method in accordance with claim 1 furthercomprising: generating a first functional image using data regarding afirst contrast agent; and generating a second functional image usingdata regarding a second contrast agent.
 3. A method in accordance withclaim 2 further comprising registering the first functional image withthe second functional image.
 4. A method in accordance with claim 3further comprising generating a ratio map on a pixel by pixel basisbetween the registered first and second images.
 5. A method inaccordance with claim 4 further comprising displaying the ratio map incolor as an overlay to a grayscale anatomical image of the lung.
 6. Amethod in accordance with claim 1 further comprising: administering afirst contrast agent in a gaseous state to the patient; andadministering a second contrast agent in a liquid state to the patient.7. A method in accordance with claim 6 wherein said administering afirst contrast agent comprises administering a first contrast agentcomprising Xenon.
 8. A method in accordance with claim 7 wherein saidadministering a second contrast agent comprises administering a secondcontrast agent comprising Iodine or Gadolinium.
 9. A method inaccordance with claim 1 further wherein said scanning comprises scanningthe patient at Total Lung Capacity (TLC).
 10. A method in accordancewith claim 1 wherein to generate the first and second images, saidmethod further comprises decomposing the acquired data.
 11. A method inaccordance with claim 10 further comprising performing a Basis MaterialDecomposition (BMD) of the acquired data.
 12. A method in accordancewith claim 10 further comprising performing a Computed Tomography (CT)Difference Decomposition of the acquired data.
 13. A method inaccordance with claim 10 further comprising performing a Compton andPhotoelectric Decomposition of the acquired data.
 14. A method inaccordance with claim 10 further comprising performing a LogarithmSubtraction Decomposition of the acquired data.
 15. A Multi-EnergyComputed Tomography (MECT) System comprising: a radiation source; aradiation detector; and a computer operationally coupled to saidradiation source and said radiation detector, said computer configuredto: receive data regarding a first energy spectrum of a scan of a lungof a patient; receive data regarding a second energy spectrum of thescan of the lung; generating a first functional image using dataregarding a first contrast agent; and generating a second functionalimage using data regarding a second contrast agent.
 16. A MECT system inaccordance with claim 15 wherein said computer further configured toperform a Compton and photoelectric decomposition of the received data.17. A MECT system in accordance with claim 15 wherein said computerfurther configured to perform a Basis Material Decomposition (BMD) ofthe received data.
 18. A MECT system in accordance with claim 15 whereinsaid computer further configured to perform a Computed Tomography (CT)Difference Decomposition of the received data.
 19. A MECT system inaccordance with claim 15 wherein said computer further configured toperform a Logarithm Subtraction Decomposition of the received data. 20.A MECT system in accordance with claim 15 wherein said computer furtherconfigured to generate a ratio map on a pixel by pixel basis between theregistered first and second images.
 21. A MECT system in accordance withclaim 20 wherein said computer further configured to display the ratiomap in color as an overlay to a grayscale anatomical image of the lung.22. A Multi-Energy Computed Tomography (MECT) System comprising: aradiation source; a radiation detector; and a computer operationallycoupled to said radiation source and said radiation detector, saidcomputer configured to: receive data regarding a first energy spectrumof a scan of a lung of a patient; receive data regarding a second energyspectrum of the scan; and decompose the received data to generate dataregarding a plurality of contrast agents.
 23. A computer readable mediumencoded with a program configured to instruct a computer to: receivedata regarding a first energy spectrum of a scan of a lung of a patient;receive data regarding a second energy spectrum of the scan; anddecompose the received data to generate data regarding a plurality ofcontrast agents.
 24. A computer readable medium encoded with a programconfigured to instruct a computer to: scan a lung of a patient with aMulti-Energy Computed Tomography (MECT) system to acquire data regardinga first contrast agent in a gaseous medium and a second contrast agentin a liquid medium; generate a first functional image using dataregarding the first contrast agent; and generate a second functionalimage using data regarding the second contrast agent.
 25. A method forobtaining data, said method comprising: administering a gaseous contrastagent to a patient; administering a liquid contrast agent to thepatient; and imaging the patient to obtain data regarding the gaseouscontrast agent and the liquid contrast agent in a single dataacquisition process.
 26. A method in accordance with claim 25 whereinsaid imaging comprises imaging the patient to substantiallysimultaneously obtain data regarding the gaseous contrast agent and theliquid contrast agent in a single data acquisition process.